RESEARCH COMMUNICATIONS
Assessment of driver vision functions
in relation to their crash involvement
in India
Ashish Verma1,5,*, Neelima Chakrabarty2,
S. Velmurugan2 , B. Prithvi Bhat3 ,
H. D. Dinesh Kumar1 and B. Nishanthi4
1
Department of Civil Engineering and 5 Centre for Infrastructure,
Sustainable Transportation and Urban Planning,
Indian Institute of Science, Bengaluru 560 012, India
2
Traffic Engineering and Safety Division, Central Road Research
Institute, Mathura Road, New Delhi 110 025, India
3
Central Institute of Road Transport, Pune 411 026, India
4
Department of Civil Engineering, National Institute of Technology,
Tiruchirappalli 620 015, India
Among the human factors that influence safe driving,
visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the
effect of visual functions of drivers in India on their
road crash involvement. Experiments were conducted
to assess vision functions of Indian licensed drivers
belonging to various organizations, age groups and
driving experience. The test results were further
related to the crash involvement histories of drivers
through statistical tools. A generalized linear model
was developed to ascertain the influence of these traits
on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision,
depth perception, contrast sensitivity, acuity and
phoria were found to influence their crash involvement rates. In India, there are no efficient standards
and testing methods to assess the visual capabilities of
drivers during their licensing process and this study
highlights the need for the same.
Keywords: Crash involvement, driver licensing, generalized linear modelling, visual functions.
Human functional failures along with their defective interactions with factors such as human, vehicle and environment are the key reasons for road accidents.
Human functions with respect to driving primarily
include perceptual and/or cognitive performance such as
visual performance, auditory skills, bio-mechanical skills,
speed judgment and adaption, reaction time, attention,
etc. 4–6. They can be broadly classified into two categories – physical and psychological. The present work
focuses on identifying the relation between visual functions and crash involvement propensity of drivers in
India.
Physical functions of drivers are important parameters
in evaluating their safe driving abilities7. Vision skills are
among the prominent physical functions that assist a
driver in perceiving traffic situations. These functions are
difficult to quantify and to consider them in road safety
evaluation is a difficult task. In heterogeneous and complex traffic conditions commonly witnessed in India,
drivers need to remain vigilant throughout, to safely
respond to vehicles of different sizes coming their way
abruptly from any direction. The complexities further
magnify while driving heavy-vehicles. This has caused an
increasing number of heavy-vehicle crashes in many
Indian cities8,9. Assessing the influence of visual abilities
on crash involvement is essential in identifying the
underlying causes of accidents due to driver fault.
A simple, multi-disciplinary test comprising of assessment of vision and cognitive tests, hazard perception and
change detection tests was found to have a significant
capacity to evaluate how safe or unsafe a driver is10. To
assess visual fitness of a driver, visual acuity, contrast
sensitivity and peripheral vision form critical components11. Impairment in visual skills was found to be a significant causal factor for road crashes in drivers above the
age of 70 years12.
Several studies have been conducted worldwide to investigate the influence of visual skills on crash propensity.
DRIVING typically forms the primary and preferred
approach of travel in many countries around the world1,
the ill consequences of which are road crashes. According
to the report by the Ministry of Road Transport and
Highways, Government of India2, driver fault forms a
significant share of the causes of road accident in India.
Figure 1 shows the causal factors of road accidents in
India in 2013, along with the percentage share.
Human functional failure can be assessed by identifying the limits in human functions that allow a person to
adapt to changing situations, for example, experience,
visual abilities, risk taking behaviour, etc. With respect to
driving, human functional failures can arise from endogenous (inabilities of drivers) and/or exogenous factors
(environment which influences endogenous factors)3.
*For correspondence. (e-mail: ashishv@civil.iisc.ernet.in)
CURRENT SCIENCE, VOL. 110, NO. 6, 25 MARCH 2016
Figure 1.
Causes of road accidents in India (2013).
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Drivers with binocular visual acuity are found to have a
higher crash risk compared to those with normal vision.
In an experiment conducted by Hofstetter 13, persons with
binocular visual acuity problems reported double the accident risks compared to those with normal vision. Estimation of effect of binocular vision on road crash
distributions of taxi drivers revealed that the average
crashes per year were more in drivers with problems in
binocular vision14. Recent research also supports the association of visual impairment and motor vehicle crashes,
specifically in older drivers12.
Depth perception plays an essential role in judging the
speed of oncoming vehicles while driving. Inabilities
in speed judgment may contribute to crash risks15.
Researchers also believe that colour vision and glare
recovery strongly associate with poor driving performances16,17. Protanopia, defined as red–green colour blindness, is considered critical in the Australian driver
licensing procedure. Since 1994, any person with protanopia is restricted from getting commercial driving
licence in Australia. Studies reveal that regardless of
severity, protanopia highly influences the risk of road
accidents18.
Since many roads in India are undivided, overtaking
vehicles often come in conflict with oncoming vehicles
from the opposite end. In a road accident investigation
study conducted on national highways, it was observed
that all the nine head-on collisions observed on undivided
highways were mainly due to overtaking vehicles entering into the oncoming vehicle lane19. Tendency of not
maintaining safe stopping sight distance is also a drawback among many Indian drivers, leading to risky situations on Indian roads. In such cases satisfactory depth
perception becomes important in ensuring the safety of
drivers.
Glare can be defined as the sensation caused when
bright light is flashed in front of one’s eyes, obstructing
his/her vision for a couple of seconds. This is a common
phenomenon witnessed in night-time driving due to the
use of high beam lights. Time taken to recovery from this
glare varies in individuals depending on their age and
vision conditions. Glare increases reaction time in drivers, thereby influencing their safety in a negative manner20,21. Again, due to the presence of many undivided
roads in India, acceptable glare recovery is important to
avoid collisions.
In simple terms, contrast sensitivity can be defined as
the ability to distinguish between an object from its background. Studies have shown that persons with contrast
sensitivity impairment restrict themselves from driving,
thereby reducing their annual mileage. This self-regulation
is mainly seen due to the increased risk of motor vehicle
collisions22. Also, depth perception of on-coming vehicles is affected by contrast sensitivity23–25. Influence of
phoria on driving performance was ascertained in the studies conducted by Burg26.
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Performance of drivers with central field of vision
impairment and normal peripheral vision was evaluated
by Lamble et al.27. It was observed that the reaction time
of these drivers was higher compared to those with
normal vision. Also, persons with central vision loss had
a greater likelihood of involving in night-time crashes28.
Drivers with binocular visual field loss were found to
have a higher crash and conviction risk compared to those
with normal vision29.
Table 1 summarizes the significance of each of the
above-mentioned vision parameters in relation to driving.
Vision test is an essential component of commercial
driver licensing in the United States. All states in the US
have visual acuity requirements for licensure, and all but
three have set the minimum ‘best corrected visual acuity’
(BCVA) requirement at 20/40 in the better eye. Georgia
requires a BCVA of at least 20/60 in at least one eye; for
New Jersey and Wyoming, the requirement is 20/50. For
the 34 states with a binocular horizontal visual field
requirement, 15 stipulate 140; for the other 19 states, the
range is from 105 to 130; Maine requires 150. Several
states list the horizontal dimension of the visual field of
applicants with only one useful eye; this ranges from 55
(Kansas) to 105 (Arkansas). Some states, including
North Carolina and Texas, do not issue any driver’s
licence to a person with homonymous hemianopia (loss
of vision in the right half or left half of both eyes). Only
Kentucky has a vertical visual field requirement: 25
above and below the fixation point30.
In the United Kingdom, separate vision test standards
are followed for private driver licence and commercial
driving licence (for bus and lorry drivers) applicants. For
private driver licence, a minimum visual acuity of 6/12
for both eyes, as measured in Snellen’s chart is required.
Also, adequate field of vision that is attested by an ophthalmologist is essential. For bus and lorry drivers, visual
acuity of 6/7.5 at least in the best eye and 6/60 in the
other is mandated. Horizontal field of vision of 106,
with extensions not less than 70 towards left and right
and 30 above and below, with no defects in the central
field of 30 is also a must31.
Australia also follows separate vision requirements for
private diver licence and commercial driving licence. A
minimum of 6/12 visual acuity in the better eye or both
eyes is essential to avail unconditional private driving
licence. Conditional licence is considered for applicants
who meet these standards with corrective lenses. For
commercial driving licence, a minimum visual acuity of
6/9 in the better eye and 6/18 in the worse eye is required.
For applicants with visual acuity worse than 6/24, driver
licence is rejected. Horizontal field of vision extending
up to 110 and 10 respectively, above and below the
horizontal midline is mandatory for private driver licence,
whereas for commercial licence it is 140 and 10
respectively, above and below the horizontal midline.
Colour vision, except for protanopia, is not a mandatory
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RESEARCH COMMUNICATIONS
Table 1.
Visual parameters
Characteristics of vision skills in relation to traffic situations
General characteristics
Characteristics in relation
to traffic situations
Inputs from the literature review
Visual acuity
Ability to see small details clearly Reading distant traffic signs
Defects in visual acuity results
in doubled crash risk
Colour vision
Distinguishing different colours
Identification of traffic signals
Negatively affects driving
performance
Phoria
Coordination of both eyes to
correctly identify the
placement of an object ahead
To identify the position of a
vehicle or an obstruction in
front of the driver correctly
Affects driving performance
Depth perception
Judgement of distance between
objects
Passing on two-lane road with
oncoming traffic
Defects in depth perception
pose serious problems while
overtaking
Contrast sensitivity
Seeing objects in similar
brightness as that of colour
Detecting dark-coloured
pedestrians at night
Poor contrast sensitivity
increases risk of motor vehicle
collision
Glare recovery
Ability to resist and recover
from glare
Reduction in visual performance
due to headlight glares
Poor glare recovery
significantly increases reaction
time resulting in accident risk
Peripheral vision
Detection of objects at the
sides of the visual fields
Seeing two wheelers
approaching from sides
Defects in visual field increase
reaction time of drivers and
likelihood of night-time crashes
Source: Traffic Engineering Hand Book, Institute of Transportation Engineers, 1999, 5th edn and previous literature.
requirement in the Australian driver licensing procedure
for private vehicles32.
India follows a ‘single-phase licensing system’, which
recommends a single phase of driver education and training prior to the written and driving test. Driver education
is not mandatory and physical fitness of candidates with
respect to visual abilities, hearing, etc. is not evaluated
before issuing driver licence. Only the manoeuvring abilities of drivers are considered sufficient for granting the
licence33.
Among the above-mentioned visual parameters, acuity
is the only parameter evaluated as part of the vision test
conducted to issue driving licence in India. According to
the Motor Vehicle Act 1988 and Central Motor Vehicles
Rules 1989, a self-declaration, medical certificate from a
registered medical practitioner is sufficient to qualify in
the vision test for driver licence, making the law relaxed.
Also, the laws are similar for all, irrespective of age and
individual characteristics5. These lacunae in the present
system of driver licensing need immediate attention in
order to address road safety issues in India.
The standards followed in other countries may not be
directly applicable in aptly assessing driver visual capabilities in India. Therefore, there is an inherent need for
extensive research focusing on the area of road safety.
Considering these issues, the following objectives have
been formulated for the present study to emphasize on the
importance of vision functions of drivers influencing road
crash involvement in India.
CURRENT SCIENCE, VOL. 110, NO. 6, 25 MARCH 2016
 Evaluating the influence of vision parameters of the
drivers on their road crash involvement in India.
 To identify critical driver vision parameters affecting
safe driving ability in Indian conditions.
It is evident from the past literature that ‘visual functions’
are among the crucial physical parameters in relation to
safe driving performance. This study attempts to assess
the effect of these parameters on crash involvement of
Indian drivers.
Three hundred and eighty seven Indian drivers belonging to different organizations, age groups and driving
experience volunteered for the study. The sample included drivers from the Karnataka State Road Transport
Corporation (KSRTC), which is one of the major public
transport undertakings in India established in 1961; Bangalore Metropolitan Transport Corporation (BMTC),
which is a Government agency that operates the public
transport bus service within Bengaluru, India; Vijayanand
Roadlines Limited (VRL), which is one of the leading
private business groups in road transportation and logistics in Karnataka, India along with some volunteers from
Indian Institute of Science (IISc), Bengaluru, and learner
licence applicants and licence renewal aspirants at the
Road Transport Office (RTO), Yeshwanthpur, Bengaluru.
The random sample has been categorized based on age
to confirm whether there is reasonable representativeness
of the population. Table 2 gives details of sample size
with respect to age.
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Table 2.
Sampling details
Sample
Organization
Category of vehicle driven/gender
Number of drivers
Percentage
KSRTC
Bus drivers/male
20–30
31–45
46–60
Total
(  = 38.1;  = 9.16)
40
80
40
160
25
50
25
100
BMTC
Bus drivers/male
20–30
31–45
46–60
Total
(  = 42.82;  = 8.01)
4
47
27
78
5.13
60.26
34.62
100
VRL
Bus and freight vehicle drivers/male
20–30
31–45
46–60
Total
(  = 36.9;  = 8.64)
11
26
13
50
22
52
26
100
IISc
Private vehicle drivers/male and female
20–30
31–45
46-60
Total
(  = 37.14;  = 12.51)
27
16
14
57
47
28
25
100
RTO
(Learner/driver/renewal licence applicants)
private vehicle drivers/male and female
20–30
31–45
46–60
Total
(  = 31.81;  = 11.79)
25
11
7
43
104
46
29
100
20–30
31–45
46–60
Total
(  = 129;  = 44.24)
106
180
101
27
47
26
387
100
Total sample
Personal details and road crash histories of tested drivers were obtained from organizational databases. For
some samples such as personal vehicle drivers from IISc
and RTO, where organizational databases were unavailable, a structured questionnaire was used to collect accident history information from the participants. As drivers
participated in the study voluntarily, they were willing to
provide data. The data were used to relate the vision test
results to the crash involvement tendency of the tested
drivers. The collected data included age of the driver,
number of years of driving experience and number of
crashes he/she has been involved in.
Driver vision skills were tested using ‘DVS-GT Deluxe
Vision Screener – Model # 1158WE’ instrument. The
visual functions tested included visual acuity, colour
vision, phoria, night vision, depth perception, contrast
sensitivity, glare recovery, peripheral vision and vertical
field of vision. Appendix 1 provides the test criteria used
to evaluate the drivers.
The tested drivers were categorized as acceptable (1)
or unacceptable (2) based on test results. The vision eval1066
Age category (years)
uation standards adopted in this study are followed
worldwide by ophthalmologists for general vision testing
and also in the licensing system of some countries (for
example: Washington, USA) to screen applicants for
driver licence.
The data obtained during the study were tabulated and
coded for further analysis. Ratio analysis and z-test of the
sample were conducted. A generalized linear model
(GLM) was developed using univariate analysis of
variance (ANOVA) and one-way ANOVA with repeated
measures. GLME is an extension of classic linear modelling incorporating response variables that follow any
probability distribution in the exponential family34,
initially coined by Nelder and Wedderburn. The explanatory variables in this study (vision test results) were
qualitative and of categorical form, whereas the response
variables were quantitative (number of crashes). GLM
was found to be the most appropriate method for such
data types, whose means do not follow normal distribution and instead are multiplicatively related to the
explanatory variables35.
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Figure 2.
Ratio analysis results.
The vision test results of all the above-mentioned samples have been summarized and the percentage of road
crash involvement of the tested drivers with respect to the
vision test results has been obtained from ratio analysis
(Figure 2).
The vision test results reveal that out of the 160
KSRTC drivers tested, 101 have at least one visual
defect, i.e. 63.75% of the drivers did not satisfy the minimum vision requirements for driving. A simple comparison of the road crash histories of the drivers to the vision
test results shows that the crash involvement rates are
high (up to 87%) in drivers categorized as ‘unacceptable’.
The number of BMTC drivers involved in road crashes
with unacceptable vision standards is high (58.3%) when
compared to those with acceptable visual standards.
Among 50 drivers tested from VRL, 50% qualified the
required standards, whereas the other 50% failed in at
least one of the tested vision parameters. Fifty-six volunteers (both male and female) from IISc, including professors, research students and administrative staff were
tested for vision. It is important to note that the crash histories of these tested subjects were obtained from selfreports. The vision test results and the road crash details
showed that the drivers with visual defects were involved
CURRENT SCIENCE, VOL. 110, NO. 6, 25 MARCH 2016
in a relatively higher number of road crashes compared to
those with normal vision. Forty-three learning licence/
driver licence/licence renewal applicants from the RTO at
Yeshwanthpur, were also tested as a part of the study.
Twenty-seven of them qualified with acceptable visual
standards, while 16 did not. Significant number of road
crashes of novice drivers was observed in this sample
group, although they do not have a permit to ride.
Leniency of the present licensing system and traffic law
enforcement methods in India are depicted in these cases.
Table 3 shows the cumulative test results of the entire
sample of 387 drivers. More than half of the entire sample (52%) failed in at least one of the vision parameters
tested. The percentage of crash involvement of subjects
with at least one visual disability was significantly higher
(81%) than those without visual disability.
Two-tailed z-test was also conducted to verify whether
there is significant difference between the crash rates of
drivers with visual defects and those with normal vision.
Table 4 presents the z-test results of the entire sample
based on the following hypothesis: (i) null hypothesis,
H0 : 0 = 1 and (ii) alternate hypothesis, H1 : 0  1,
where 0 is the mean of the sample of number of accidents by drivers with visual defects, and 1 is the mean of
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Table 3.
Aggregate vision test results
Vision test results
Vision parameters
Unacceptable
Left eye acuity
Right eye acuity
Night vision
Acuity (both eyes)
Colour vision
Phoria
Contrast sensitivity
Glare recovery
Depth perception
Peripheral vision
Vertical field of vision
Drivers with unacceptable
standard in at least one
of the tested parameters
45 (12%)
60 (16%)
39 (10%)
38 (10%)
56 (14%)
6 (2%)
17 (4%)
25 (6%)
111 (29%)
6 (2%)
85 (22%)
201 (52%)
Table 4.
Parameters
Mean
Variance
Observations
Hypothesized mean
difference
z
P(Z  z) one-tail
Z critical one-tail
P(Z  z) two-tail
Z critical two-tail
Crashes involved
Acceptable
342
327
348
349
331
381
370
362
276
381
302
186
Unacceptable
Acceptable
Unacceptable
44
62
36
36
33
2
18
23
106
6
77
162
217
199
225
225
228
259
243
238
155
255
184
99
98
103
92
95
59
33
106
92
95
100
91
81
(88%)
(84%)
(90%)
(90%)
(86%)
(98%)
(96%)
(94%)
(71%)
(98%)
(78%)
(48%)
z-test results
Accidents by drivers
with visual defects
0.803191489
1.132182273
188
0
Accidents by drivers
without visual defects
0.587939698
1.112177047
199
1.997609288
0.022879518
1.644853627
0.045759036
1.959963985
Table 5.
Descriptive statistics
Vision defect
1 – Sample with at least one
vision defect
2 – Sample with no vision defect
Total
Mean
Standard deviation
N
0.59
1.055
199
0.80
0.69
1.064
1.063
188
387
the sample of number of accidents by drivers without any
vision defects (normal vision).
Here, z-statistics is greater than the z critical in the
two-tail z-test. This implies that the obtained z-statistics
lies in the rejection area of the normal distribution of the
sample. Hence, the null hypothesis H0 can be rejected,
which leads to the acceptance of the alternate hypothesis
H1. The result of the analysis is that the means of the
samples of the number of accidents of drivers with and
without vision defects are different. This indicates that
there is significant influence of vision defects over crash
association of tested drivers.
GLM was also done to verify whether there is significant difference between the crash rates of drivers with
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Percentage of crash involvement
Acceptable
63
61
65
64
69
68
66
66
56
67
61
53
visual defects and those with normal vision. Tables 5 and
6 provide the results.
The results show there is significant influence (  values <0.05.) of vision defects on crash involvement of
tested drivers. Also, using GLM, the influence of particular visual defects on the crash rate of drivers has been
analysed. Tables 7 and 8 present GLM results.
Here, dependent variable is the number of accidents
and the independent variables (fixed factors) are the visual defects – acuity, binocular, colour blindness, phoria,
depth perception, contrast sensitivity, glare recovery,
peripheral vision, nasal vision and vertical vision. The
effect of the fixed factors (visual defects) on the dependent variable (number of accidents) is observed using
GLM one way ANOVA with repeated measures on the
data.
A repeated measures ANOVA with a greenhouse–
Geisser correction revealed that mean number of accidents differed statistically significantly between vision
defect points (F(6.276, 2422.50) = 36.602, P < 0.0005).
Post hoc tests using Bonferroni correction revealed that
individual vision defects have influence over the number
of accidents. The decreasing order of the influence being
phoria, peripheral vision, contrast sensitivity, binocular
vision, glare recovery, acuity, vertical vision, colour
blindness, nasal vision and depth perception.
The primary goal of the present study was to identify
and assess the effect of visual disabilities of drivers on
their crash involvement. In the present study, the following uncertainties were observed in the collected data: (a)
The crash histories of private vehicle drivers (from IISc
and RTO) were collected through self-reports. The data
are based on the assumption of their truthfulness. (b) The
maximum number of crashes of the tested drivers from
KSRTC, BMTC and VRL does not exceed five. This is
due to the fact that drivers with more than five crashes
are usually dismissed from these organizations. Also, the
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Table 6. Test of between-subject effects
Source
Type III sum of squares
Corrected model
Intercept
Vision defect
Error
Total
Corrected total
a
4.479
187.084
4.479
431.929
622.000
436.408
a
df
Mean square
1
1
1
385
387
386
4.479
187.084
4.479
1.122
F
3.992
166.757
3.992

0.046
0.000
0.046
Partial eta squared
0.010
0.302
0.010
R squared = 0.010 (adjusted R squared = 0.008).
Table 7.
Descriptive statistics
Parameters
Mean
Standard deviation
N
Left eye acuity
Right eye acuity
Binocular night mode
Binocular day mode
Colour test
Phoria
Depth perception
Contrast sensitivity
Glare recovery
Peripheral vision
Nasal vision
Vertical upward vision
Vertical downward vision
1.94
1.95
1.97
1.96
1.92
1.99
1.75
1.97
1.95
1.98
1.79
1.93
1.94
0.237
0.216
0.180
0.199
0.276
0.101
0.435
0.166
0.222
0.124
0.407
0.255
0.241
387
387
387
387
387
387
387
387
387
387
387
387
387
complete crash histories of the tested subjects (before
joining the organization) were not available.
The results show a significant relation between roadcrash tendencies of drivers and visual defects such as
phoria, peripheral vision and contrast sensitivity.
It is important to note in the present study that drivers
with no visual defects were also involved in crashes. In
these cases, the causal factors other than vision such as
environment, road condition, psychological condition of
the driver, etc. may have been the significant underlying
cause for the road crashes.
Another interesting aspect observed from the study is
that many of the licensed drivers tested did not qualify
the minimal vision standards. A similar study conducted
at Guwahati, Assam also identified several shortcomings
in the visual capabilities of licensed drivers5. It was
observed that out of the 189 licensed drivers tested for
vision, 3% failed in phoria, 12% in the depth judgement,
7% in glare recovery, 5% in nasal vision, 15% in acuity,
5% in night vision, and 5% in colour vision. These results
depict the flexibility in the current licensing practices,
which may ultimately reduce driving safety. The test
results emphasize the need for stringent scrutiny, particularly of the commercial vehicle drivers prior to their
licensing and employment.
In practice, visual acuity, visual field and colour vision
are the mandatory vision requirements in many of the International driver licensing systems, including Canada,
CURRENT SCIENCE, VOL. 110, NO. 6, 25 MARCH 2016
Germany, USA and Australia. Table 9 shows a comparison between some of the vision requirements, nationally
(with respect to India) and internationally.
Apart from the aforementioned parameters the influence of phoria, contrast sensitivity, depth perception, etc.
has been closely scrutinized in this study and is realized
to have critical influence on road safety.
From the present study it is empathized that vision
tests are to be made an integral part of the recruitment
process of drivers, especially for commercial and public
services. In order to address this issue of road safety in
the present scenario, vision skill evaluation and vision
rectification programmes need to be conducted for the
drivers already employed as a part of safe driving performance enhancement programmes. Awareness sessions
should also be considered as a vital step towards providing a platform for the drivers for self-realization and
assessment of their visual limitations and further
assistance in seeking medical aid in resolving the problem. Along with these measures, planned scheduling of
drivers with night vision and glare recovery problems to
prevent them from night-time driving can be taken up to
improve safety of passengers and other road users.
Road safety is a critical issue that needs focus in this
era of increased road-crash deaths. India is one of the
perilous countries in terms of road fatalities in the world.
The motivation behind this study was to scientifically
analyse the effect of vision functions on road crashes.
Different visual functions and their influence on roadcrash involvement were reviewed by assessing them with
the help of ‘DVS-GT deluxe vision screener’ instrument.
A total of 387 drivers from various organizations volunteered for the study. Road-crash histories of the subjects
were also collected. The results were analysed using
statistical tools.
This study helps in understanding the importance of
visual requirements for safe driving. It highlights the
importance of addressing the road safety issue collectively
using 3Es: education, engineering and enforcement with
respect to driver vision as well. The method adopted in
the study proves to be useful in screening candidates during the issue of driver licences.
Vision parameters other than the general acuity such as
peripheral vision, contrast sensitivity, glare recovery, etc.
have been found to effect safety performance of drivers.
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Table 8. Tests of between-subjects effects
Source
Type III sum of squares
df
Mean square
F

Partial eta sqaured
18655.803
59.120
1
386
18655.803
0.153
121804.954
0.000
0.997
Intercept
Error
Table 9.
Vision parameters
Visual acuity
Specifications
International standards
No visual acuity-based objection. Provision of unrestricted driving
licence even if acuity could be further improved by glasses or lenses
<6/12 (<0.5) to
6/60 (0.1)
Individual consideration, which may result in restriction or denial.
Evaluation should include visual and non-visual factors and a road
test when in doubt. Some licences may be granted
No driving licence
120 horizontal,
40 vertical or better
No visual field-based objection. Provision of unrestricted driving
licence, provided that the field is about evenly divided around fixation
and that no attention-related problems are identified
Individual consideration, which may result in restriction or denial.
Evaluation should include visual and non-visual factors and a road
test when in doubt. Some licences maybe granted, some may not
Worse
Colour test
Indian standards
6/12 (0.5) or better
<6/60 (<0.1)
Field of vision
Vision requirement standards for safe driving
To identify the
difference between
red and green
Required to pass colour test
6/18 or better
Not
considered
Not considered
Source: Vision requirements for driving safety – International Council of Ophthalmology, 2005.
Appendix 1.
Type of test
Criteria used to categorize vision screening results
Test procedure
Acceptable
Unacceptable
Visual acuity – right eye,
left eye, and for both
eyes (night and day mode)
The subject is made to identify numbers of varying sizes
that appear on the screen.
Vision range between
6/6 and 6/12.
Vision range more
than 6/12.
Colour test (green, red and
yellow)
The subject is asked to identify the colours he/she is
able to see on the screen.
If subject identifies all
three colours.
If the subject does not
identify colours correctly.
Phoria/Binocular vision
The subject is made to identify the placement of a red
dot that is visible on the screen.
Dot within rectangle.
Dot outside the rectangle.
Depth perception (subject is
asked to identify six traffic
signs and asked which is
farther and which is nearer)
The subject is asked to identify some of the road sign
targets placed at different positions and is also asked to
distinguish the targets that appear relatively closer
or farther.
If both near and far signs
are observed correctly.
If the subject fails to
identify the position of
close and far away signs.
Contrast sensitivity
In night mode, the subject is presented with numbers
in three columns with an acuity of 6/21,
each column set at different contrast.
If subject is able to read
within 40% contrast.
If the subject is unable to
read within 40% contrast.
Glare recovery
In night mode, the subject is exposed to illuminated
flash of light for a period of 3 sec, and asked to
read numbers on screen within 5 sec.
If the subject identifies at
least six out of seven
numbers in any one line.
If the subject fails to
read at least six out of the
given numbers in any line.
Horizontal field vision test
The subject is asked to identify LED targets kept at
55, 70 and 85 angles. This test is conducted for
each eye separately.
If the subject identifies
the LED targets
@ 70 or 85.
If the subject fails to
identify all targets
at 70 or 85.
Vertical field vision test –
both upper and lower
The subject is asked to identify LED targets kept at
35 angle in the vertical plane. This test is conducted
for each eye separately.
If the subject identifies
the target.
If the subject fails to
identify the target.
Source: Keystone DVS-GT Deluxe Record Form for use with Model 1158.
*Note: 6/6 vision refers to normal vision indicated by the ability to accurately read the vision test chart placed at a distance of 6 m from the eye. 6/12 vision refers to the ability to accurately read the vision test chart placed at a distance of 6 m, which a normal vision person can read from a distance of 12 m.
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RESEARCH COMMUNICATIONS
These tests are required to be made mandatory for commercial and public service vehicle drivers to begin with.
There is a huge need to amend the Indian standards of
vision testing for drivers. The governing laws in India
with respect to driver licensing procedures need to be
appropriately amended to create safe drivers by strict visual screening before issuing driving licence. Persons with
unacceptable standards of visual functions must either be
issued a regulated driving licence or licence must be
issued only after the problem is medically rectified, if
possible.
The present road accident investigation practices followed in India do not include a systematic methodology
to test the visual defects in the driver at the time of accident. Therefore, scientific and accurate data to correlate
the vision defect of drivers to their crash involvement are
unavailable. However, this can form a scope in future
studies wherein road accident investigations are conducted with assessment of visual functions of the driver,
based on which a detailed study can be conducted. An
enhanced and representative sample size of drivers from
all vehicle categories and driving experiences is required
to obtain results that are more representative. Also, other
physical parameters such as auditory skills, limb strength,
reaction time, etc. and psychological parameters such as
sensation seeking, driver fatigue, aggression, etc. play an
important role in safe driving activity. Therefore, a
thorough study is necessary to clearly understand the
effect of overall human factors on safe driving. A realtime evaluation of these psychophysical parameters
would allow a better appreciation of their influence on
driving. Experimental studies using EEG signals, heart
rate variation, etc. may be adopted in this direction.
Another important aspect that requires consideration is
the calibration of the test methodology adopted in the
present study. This is essential to assess its adaptability
for testing in Indian conditions to provide a better insight
regarding the influence of visual skills on Indian road
safety. Further, calibration of the test methodology
becomes necessary for incorporation in practical issues
such as traffic engineering, policy-making, education and
enforcement.
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ACKNOWLEDGEMENTS. We thank the Council of Scientific and
Industrial Research, New Delhi for funds (Project No. 70(0067)/
11/EMR-II). We also thank KSRTC, BMTC, VRL, IISc, Bengaluru and
RTO (Yeshwanthpur, Bengaluru) for providing sample drivers for the
study and also the required accident histories of the tested drivers.
Also, we would like to thank M-Tech students Ms N. S. L. Aparna
from NIT Trichy, and Mr S. Rohit from Reva Institute of Technology
and Management, Bengaluru for data compilation and assistance in the
analyses.
Received 5 December 2014; revised accepted 27 October 2015
doi: 10.18520/cs/v110/i6/1063-1072
Study of traffic noise in urban street
canyons of Bengaluru city
Halesh Koti1,*, G. Ranganath1 and
H. N. Rajakumara2
1
Mechanical Engineering Department,
Adhiyamaan College of Engineering, Hosur 635 109, India
2
Civil Engineering Department, R.R. Institute of Technology,
Chikkabanavara, Bengaluru 560 090, India
In urban street canyons, external noise environment is
a critical restriction to the opening of building windows for natural ventilation. The high external noise
intensities are often used to substantiate the utilization
of air conditioning systems in residential and commercial buildings. Therefore, a systematic method of
examining the noise levels in urban street canyons is
essential if the potential for natural ventilation is to be
estimated. The noise levels and natural ventilation in
urban street canyons depend on many aspects such as
*For correspondence. (e-mail: halkoti@gmail.com)
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existing street dimensions, height of buildings and
traffic density. A study has been carried out in a street
to examine the variation in noise levels vertically in
order to provide technical inputs on natural ventilation potential in urban street canyons. In this study, a
number of noise measurements were made in urban
street canyons of Bengaluru City, in residential and
commercial areas with respect to aspect ratio (height
of building/street width) changing from 1.0 to 4.0.
With the help of measured data, a statistical model
was developed. A linear regression analysis has been
used. The model can be used to predict variation of
noise level in vertical direction in urban street canyons. The variation of noise level is found to be a function of street width and height of a building above the
street level, but the highest level of reduction is almost
entirely a function of the aspect ratio. The rate of
attenuation of foreground noise (L 10) is greater than
the background noise (L90 ) with height.
Keywords: Aspect ratio, noise attenuation, traffic
noise, urban street canyon.
CANYON-like streets in urban areas vary considerably in
width and in the height of the buildings which border
them1. The facades of some of the buildings are plain and
some have balconies. A majority of buildings in residential streets as well as some of the office buildings in
commercial streets have balconies. The facades at ground
level can be even more complex. The ground floor is
generally set back with colonnades.
Some noise measurements were taken in street canyons
of Bengaluru city. The measurements were made to
assess the effect of noise level in the vertical direction
above street level. This study aims to provide guidance
about the effect on the external noise environment of the
street width, aspect ratio and the height of the location
above street level. This requires assessment of the relative significance of the direct sound and the reverberant
noise level in the street canyon. Other important factors
to be considered are the traffic density and noise associated with it in the street. The ratio of the height of the
buildings in street canyons (H) to the width of the street
(w) is known as the ‘aspect ratio’ (AR) of the street with
assumption that the buildings on either side are at same
height. However in reality, this may not be the case.
In this study, the average height of the buildings in
street canyons has been taken to get AR = (H1 + H2 )/2w
(Figure 1). The facade of building also varies considerably with and without balconies.
Noise measurements were made in Bengaluru at nine
selected street canyons comprising residential zone,
commercial zone, silent zone and heavy traffic zone
(Table 1). In each street, canyon measurements were
taken outside the windows of buildings. The aim of these
noise measurements was to assess the vertical variation of
noise level with respect to measurement location above
CURRENT SCIENCE, VOL. 110, NO. 6, 25 MARCH 2016